Evaluation of a newly designed deep learning-based algorithm for automated assessment of scapholunate distance in wrist radiography as a surrogate parameter for scapholunate ligament rupture and the correlation with arthroscopy.

PURPOSE: Not diagnosed or mistreated scapholunate ligament (SL) tears represent a frequent cause of degenerative wrist arthritis. A newly developed deep learning (DL)-based automated assessment of the SL distance on radiographs may support clinicians in initial image interpretation. MATERIALS AND METHODS: A pre-trained DL algorithm was specifically fine-tuned on static and dynamic dorsopalmar wrist radiography (training data set n = 201) for the automated assessment of the SL distance. Afterwards the DL algorithm was evaluated (evaluation data set n = 364 patients with n = 1604 radiographs) and correlated with results of an experienced human reader and with arthroscopic findings. RESULTS: The evaluation data set comprised arthroscopically diagnosed SL insufficiency according to Geissler's stages 0-4 (56.5%, 2.5%, 5.5%, 7.5%, 28.0%). Diagnostic accuracy of the DL algorithm on dorsopalmar radiography regarding SL integrity was close to that of the human reader (e.g. differentiation of Geissler's stages ≤ 2 versus > 2 with a sensitivity of 74% and a specificity of 78% compared to 77% and 80%) with a correlation coefficient of 0.81 (P < 0.01). CONCLUSION: A DL algorithm like this might become a valuable tool supporting clinicians' initial decision making on radiography regarding SL integrity and consequential triage for further patient management.

Transcriptomics-inferred dynamics of SARS-CoV-2 interactions with host epithelial cells.

Virus-host interactions can reveal potentially effective and selective therapeutic targets for treating infection. Here, we performed an integrated analysis of the dynamics of virus replication and the host cell transcriptional response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using human Caco-2 colon cancer cells as a model. Time-resolved RNA sequencing revealed that, upon infection, cells immediately transcriptionally activated genes associated with inflammatory pathways that mediate the antiviral response, which was followed by an increase in the expression of genes involved in ribosome and mitochondria function, thus suggesting rapid alterations in protein production and cellular energy supply. At later stages, between 24 and 48 hours after infection, the expression of genes involved in metabolic processes-in particular, those related to xenobiotic metabolism-was decreased. Mathematical modeling incorporating SARS-CoV-2 replication suggested that SARS-CoV-2 proteins inhibited the host antiviral response and that virus transcripts exceeded the translation capacity of the host cells. Targeting kinase-dependent pathways that exhibited increases in transcription in host cells was as effective as a virus-targeted inhibitor at repressing viral replication. Our findings in this model system delineate a sequence of SARS-CoV-2 virus-host interactions that may facilitate the identification of druggable host pathways to suppress infection.

MRI-based torsion measurement of the lower limb is a reliable and valid alternative for CT measurement: a prospective study.

PURPOSE: The aim of this study was to compare MRI-based torsion measurements of the lower limb to a well-established CT-based assessment in a prospective inter- and intraindividual approach. METHODS: A total of 26 patients (age 28.8 years ± 11.0) were enrolled beginning in January 2021 until August 2022. Inclusion criteria were the clinical indication for torsion measurement of the lower limb. CT and MRI imaging were performed with a standard operating procedure, to ensure that all patients were examined in a standardized position. The examinations were planned on a coronal scout view based on prominent anatomical landmarks. Femoral and tibial torsion were measured individually. Torsion measurements were analysed twice: immediately after examination and after 3 weeks. Subsequently, intra-rater and parallel test reliability was calculated accordingly. RESULTS: High significant results for CT and MRI measurements for both tibia (MRI: r = 0.961; p ≤ 0.001; CT: r = 0.963; p ≤ 0.001) and femur (MRI: r = 0.980; p ≤ 0.001; CT: r = 0.979; p ≤ 0.001) were obtained by calculated intra-rater reliability, showing that measurements were highly consistent for MRI and CT, respectively. Parallel test reliability for time point 1 as well as time point 2 was also highly significant and ranged from r = 0.947 to r = 0.972 (all with p ≤ 0.001, respectively) for both tibia and femur, showing a high concordance between the two measurements. CONCLUSION: Measurement of tibial as well as femoral torsion was comparable for CT and MRI measurement. Therefore, this study supports MRI measurement as an equivalent alternative for CT measurement concerning torsional malalignment to reduce exposure to radiation. LEVEL OF EVIDENCE: Level II.

The gap height in open wedge high tibial osteotomy is not affected by the starting point of the osteotomy.

INTRODUCTION: In open-wedge high-tibial-osteotomy (OWHTO), most surgeons use a preoperative planning software and realise that they should match the intraoperative alignment correction with the preoperative plan. We aimed to determine whether there is a difference in osteotomy gap height when starting the OWHTO either 3 or 4 cm distal to the joint line. This should help to clarify whether the osteotomy starting point must exactly match the preoperative planning. METHODS: 25 patients with constitutional varus alignment were planned for OWHTO. Long-leg-standing-radiographs and mediCAD-software were used. Osteotomy was planned to a neutral Hip-Knee-Ankle angle (HKA) of 0°. The osteotomy-starting-point was either 3 or 4 cm distal to the medial joint line. The following angles were compared: mechanical medial proximal tibial angle (mMPTA), mechanical lateral distal femoral angle (mLDFA), joint line conversion angle (JCA), mechanical Tibio-Femoral angle (mTFA) or Hip Knee Ankle (HKA) angle. RESULTS: 25 Patients (18 males, 7 females) had a mean age of 62 ± 16.6 years and showed a varus-aligned leg-axis. The HKA was - 5.96 ± 3.02° with a mMPTA of 82.22 ± 1.14°. After osteotomy-planning to a HKA of 0°, the mMPTA was 88.94 ± 3.01°. With a mean wedge height of 8.08 mm when locating the osteotomy 3 cm and a mean wedge height of 8.05 mm when locating the osteotomy 4 cm distal to the joint-line, there was no statistically significant difference (p = 0.7). CONCLUSION: When performing an OWHTO aiming towards the tip of the fibula, the osteotomy starting point does not need to exactly match the planned starting-location of the osteotomy. A starting-point 1 cm more distal or proximal than previously determined through the digital planning does not alter the size of the osteotomy gap needed to produce the desired amount of correction.

Diagnostic Accuracy of 128-Slice Single-Source CT for the Detection of Dislocated Bucket Handle Meniscal Tears in the Setting of an Acute Knee Trauma-Correlation with MRI and Arthroscopy.

(1) Background: Meniscal tears are amongst the most common knee injuries. Dislocated bucket handle meniscal tears in particular should receive early intervention. The purpose of this study was to evaluate the diagnostic performance of CT in detecting dislocated bucket handle meniscal tears compared with the gold-standard MRI and arthroscopy. (2) Methods: Retrospectively, 96 consecutive patients underwent clinically indicated CT of the knee for suspected acute traumatic knee injuries (standard study protocol, 120 kV, 90 mAs). Inclusion criteria were the absence of an acute fracture on CT and a timely MRI (<6 months). Corresponding arthroscopy was assessed. Two experienced musculoskeletal radiologists analyzed the images for dislocated bucket handle meniscal tears, associated signs thereof (double posterior cruciate ligament sign, double delta sign, disproportional posterior horn sign), and subjective diagnostic confidence on a 5-point-Likert scale (1 = 'non-diagnostic image quality', 5 = 'very confident'). (3) Results: Dislocated bucket handle meniscal tears were detected on CT by standard three-plane bone kernel reconstructions with a sensitivity of 90.7% and a specificity of 99.3% by transferring the knowledge of established MRI signs. The additional use of soft-tissue kernel reconstructions in three planes increased the sensitivity by 4.0% to 94.7%, specificity to 100%, inter-rater agreement to 1.0, and the diagnostic confidence of both readers improved to a median 4/5 ('confident') in both readers. (4) Conclusions: Trauma CT scan of the knee with three-plane soft-tissue reconstructions delivers the potential for the detection of dislocated bucket handle meniscal tears with very high diagnostic accuracy.

Amount and composition of total fatty acids in red and yellow bone marrow are altered with changes in bone mineral density.

There is general consent that with decreasing bone mineral density the amount of marrow adipose tissue increases. While image-based techniques, claim an increase in saturated fatty acids responsible for this effect, this study shows an increase in both saturated and unsaturated fatty acids in the bone marrow. Using fatty acid methyl ester gas chromatography-mass spectrometry, characteristic fatty acid patterns for patients with normal BMD (N = 9), osteopenia (N = 12), and osteoporosis (N = 9) have been identified, which differ between plasma, red bone marrow and yellow bone marrow. Selected fatty acids, e.g. FA10:0, FA14:1, or FA16:1 n-7 in the bone marrow or FA18:0, FA18:1 n-9, FA18:1 n-7, FA20:0, FA20:1 n-9, or FA20:3 n-6 in the plasma, correlated with osteoclast activity, suggesting a possible mechanism how these fatty acids may interfere with BMD. Although several fatty acids correlated well with the osteoclast activity and BMD, there was not a single fatty acid contained in our fatty acid profile that can be claimed for controlling BMD, a fact that may be attributed to the genetic heterogeneity of the patients.

The Impact of Injury of the Tibial Nutrient Artery Canal on Type of Nonunion of Tibial Shaft Fractures: A Retrospective Computed Tomography Study.

RATIONALE AND OBJECTIVES: Blood supply is vital for sound callus formation. The tibial nutrient artery (TNA) is the main diaphyseal artery nurturing the tibial shaft. The objective is to investigate the impact of TNA canal (TNAC) injury on the development of atrophic, oligotrophic, and hypertrophic nonunion in patients with tibial shaft fractures. MATERIALS AND METHODS: Between January 2010 and December 2020, patients with a nonunion of a tibial shaft fracture were retrospectively included. Two readers independently evaluated the integrity of the TNAC and classified nonunion type. A multinomial regression model was utilized to evaluate if a TNAC injury has an impact on the type of nonunion. RESULTS: From an initial set of 385 patients with the diagnosis of a nonunion of the lower leg, a total of 60 patients could be finally included in the study. Most patients were males (78%), diabetic (95%), smokers (73%), and had an American Society of Anesthesiologists (ASA) score of 2 (72%). TNAC injury was noted in 24 patients (40%): an iatrogenic TNAC injury was observed in 13 (22%) patients, a traumatic TNAC injury in 11 (18%) patients. Most patients had a hypertrophic nonunion (29 patients (48%)), followed by an oligotrophic nonunion (24 patients (40%)) and lastly an atrophic nonunion (seven patients (11%)). The multinomial regression model showed that there was no impact of TNAC injury on the development of a specific type of non-union (p = 0.798 for oligotrophic vs. atrophic nonunion; p = 0.943 for hypertrophic vs. atrophic nonunion). Furthermore, patients were about four times more likely to develop an oligotrophic/hypertrophic nonunion rather than atrophic one (odds ratio 3.75 and 4.25, respectively), regardless of the presence of a TNAC injury. CONCLUSION: In the evaluated patient cohort with tibial shaft fractures, we could not find a statistically significant association between TNAC injury and type of nonunion. However, patients were almost four times more likely to develop oligotrophic or hypertrophic nonunion rather than an atrophic one although common risk factors for impaired (micro)vascular blood supply were highly prevalent in the study group. Multicenter studies with a larger number of atrophic nonunions are warranted to further evaluate this result.

Prospective intraindividual comparison of a standard 2D TSE MRI protocol for ankle imaging and a deep learning-based 2D TSE MRI protocol with a scan time reduction of 48.

PURPOSE: Magnetic resonance imaging (MRI) scan time remains a limited and valuable resource. This study evaluates the diagnostic performance of a deep learning (DL)-based accelerated TSE study protocol compared to a standard TSE study protocol in ankle MRI. MATERIAL AND METHODS: Between October 2020 and July 2021 forty-seven patients were enrolled in this study for an intraindividual comparison of a standard TSE study protocol and a DL TSE study protocol either on a 1.5 T or a 3 T scanner. Two radiologists evaluated the examinations regarding structural pathologies and image quality categories (5-point-Likert-scale; 1 = "non diagnostic", 5 = "excellent"). RESULTS: Both readers showed almost perfect/perfect agreement of DL TSE with standard TSE in all analyzed structural pathologies (0.81-1.00) with a median "good" or "excellent" rating (4-5/5) in all image quality categories in both 1.5 T and 3 T MRI. The reduction of total acquisition time of DL TSE compared to standard TSE was 49% in 1.5 T and 48% in 3 T MRI to a total acquisition time of 5 min 41 s and 5 min 46 s. CONCLUSION: In ankle MRI the new DL-based accelerated TSE study protocol delivers high agreement with standard TSE and high image quality, while reducing the acquisition time by 48%.

Ultra-low-dose CT is feasible for torsion measurement of the lower limb in patients with metal implants.

OBJECTIVES: Patients who need torsion measurement of the lower limb often have metal implants hindering e.g. MRI. A new ultra-low-dose (ULD-)CT protocol might be feasible for torsion measurement at cost of relatively low radiation exposure. METHODS: We retrospectively included all patients with clinically indicated torsion measurement in the period July 2019 to June 2021 and metal implants in the scanning field. The ULD-CT protocol comprised automated tube current time product and automated tube voltage with reference settings of 100kV/20mAs (hip), 80kV/20mAs (knee) and 80kV/10mAs (ankle). Femoral neck anteversion, tibial, intra-articular knee and overall leg torsion measurements were performed by two radiologists independently. Diagnostic confidence regarding the delineation of the relevant cortical bone was rated on a 5-point Likert scale (1 = non-diagnostic, 5 = excellent). RESULTS: 102 consecutive patients could be included (BMI 27.38 ± 5.85) with 154 metal implants. Median total dose length product of the ULD-CT-torsion measurement was 16.5mGycm [11-39]. Both readers showed high agreement with a maximum torsional difference of 4.1°. Diagnostic confidence was rated best (5/5) in 92.2% (reader 1) and 93.1% (reader 2) with a worst rating of 3/5. CONCLUSION: The new ULD-CT protocol is feasible for torsion measurement of the lower limb - even in patients with metal implants. ADVANCES IN KNOWLEDGE: Metal implants are not an obstacle for ULD-CT torsion measurements of the lower limb.

Deep Learning in the Detection of Rare Fractures - Development of a "Deep Learning Convolutional Network" Model for Detecting Acetabular Fractures. / Deep Learning in der Erkennung seltener Frakturen ­ Entwicklung eines "Deep Convolutional Neural Network" (DCNN) am Beispiel der Azetabulumfraktur.

BACKGROUND: Fracture detection by artificial intelligence and especially Deep Convolutional Neural Networks (DCNN) is a topic of growing interest in current orthopaedic and radiological research. As learning a DCNN usually needs a large amount of training data, mostly frequent fractures as well as conventional X-ray are used. Therefore, less common fractures like acetabular fractures (AF) are underrepresented in the literature. The aim of this pilot study was to establish a DCNN for detection of AF using computer tomography (CT) scans. METHODS: Patients with an acetabular fracture were identified from the monocentric consecutive pelvic injury registry at the BG Trauma Center XXX from 01/2003 - 12/2019. All patients with unilateral AF and CT scans available in DICOM-format were included for further processing. All datasets were automatically anonymised and digitally post-processed. Extraction of the relevant region of interests was performed and the technique of data augmentation (DA) was implemented to artificially increase the number of training samples. A DCNN based on Med3D was used for autonomous fracture detection, using global average pooling (GAP) to reduce overfitting. RESULTS: From a total of 2,340 patients with a pelvic fracture, 654 patients suffered from an AF. After screening and post-processing of the datasets, a total of 159 datasets were enrolled for training of the algorithm. A random assignment into training datasets (80%) and test datasets (20%) was performed. The technique of bone area extraction, DA and GAP increased the accuracy of fracture detection from 58.8% (native DCNN) up to an accuracy of 82.8% despite the low number of datasets. CONCLUSION: The accuracy of fracture detection of our trained DCNN is comparable to published values despite the low number of training datasets. The techniques of bone extraction, DA and GAP are useful for increasing the detection rates of rare fractures by a DCNN. Based on the used DCNN in combination with the described techniques from this pilot study, the possibility of an automatic fracture classification of AF is under investigation in a multicentre study.

Automated Artificial Intelligence-Based Assessment of Lower Limb Alignment Validated on Weight-Bearing Pre- and Postoperative Full-Leg Radiographs.

The assessment of the knee alignment using standing weight-bearing full-leg radiographs (FLR) is a standardized method. Determining the load-bearing axis of the leg requires time-consuming manual measurements. The aim of this study is to develop and validate a novel algorithm based on artificial intelligence (AI) for the automated assessment of lower limb alignment. In the first stage, a customized mask-RCNN model was trained to automatically detect and segment anatomical structures and implants in FLR. In the second stage, four region-specific neural network models (adaptations of UNet) were trained to automatically place anatomical landmarks. In the final stage, this information was used to automatically determine five key lower limb alignment angles. For the validation dataset, weight-bearing, antero-posterior FLR were captured preoperatively and 3 months postoperatively. Preoperative images were measured by the operating orthopedic surgeon and an independent physician. Postoperative images were measured by the second rater only. The final validation dataset consisted of 95 preoperative and 105 postoperative FLR. The detection rate for the different angles ranged between 92.4% and 98.9%. Human vs. human inter-(ICCs: 0.85−0.99) and intra-rater (ICCs: 0.95−1.0) reliability analysis achieved significant agreement. The ICC-values of human vs. AI inter-rater reliability analysis ranged between 0.8 and 1.0 preoperatively and between 0.83 and 0.99 postoperatively (all p < 0.001). An independent and external validation of the proposed algorithm on pre- and postoperative FLR, with excellent reliability for human measurements, could be demonstrated. Hence, the algorithm might allow for the objective and time saving analysis of large datasets and support physicians in daily routine.

Ultra-low dose CT for scaphoid fracture detection-a simulational approach to quantify the capability of radiation exposure reduction without diagnostic limitation.

Background: Modern CT might deliver higher image quality than necessary for fracture imaging, which would mean non-essential effective radiation exposure for patients. We simulated ultra-low dose (ULD)-CT at different dose levels and analyzed their diagnostic performance for scaphoid fracture detection. Methods: 30 consecutive high quality CT with clinically suspected scaphoid fractures were assessed. ULD-simulations were made at 20%, 10% and 5% of original dose. Three readers at different levels of experience (expert, moderate, inexperienced) expressed their diagnostic confidence (DC; 5-point-Likert-scale) and analyzed the presence and classification of scaphoid fractures within Krimmer's and Herbert's classifications. Effective radiation exposure of the original data sets and ULD-CT were calculated. Results: At 20% and 10% dose the more experienced readers reached perfect sensitivity (100%) and specificity (100%), showing perfect agreement regarding fracture classification (1.00). Diagnostic performance decreased at 5% dose (92.86% sensitivity, 100% specificity; expert reader). The inexperienced reader showed reduced sensitivity and specificity at all dose levels. At 10% dose minimal DC of all readers was 3/5 and mean calculated effective radiation exposure was 1.11 [±0.36] µSv. Conclusions: The results suggest that ULD-CT at 10% dose compared to high quality CT might offer sufficient image quality to precisely detect and classify scaphoid fractures, if moderate experience of the radiologist is granted.

[Artificial intelligence and novel approaches for treatment of non-union in bone : From established standard methods in medicine up to novel fields of research]. / Künstliche Intelligenz und Ausblick auf Anwendungsfelder in der Pseudarthrosentherapie : Von etablierten Standardmethoden in der Medizin hin zu neuen Forschungsfeldern.

Methods of artificial intelligence (AI) have found applications in many fields of medicine within the last few years. Some disciplines already use these methods regularly within their clinical routine. However, the fields of application are wide and there are still many opportunities to apply these new AI concepts. This review article gives an insight into the history of AI and defines the special terms and fields, such as machine learning (ML), neural networks and deep learning. The classical steps in developing AI models are demonstrated here, as well as the iteration of data rectification and preparation, the training of a model and subsequent validation before transfer into a clinical setting are explained. Currently, musculoskeletal disciplines implement methods of ML and also neural networks, e.g. for identification of fractures or for classifications. Also, predictive models based on risk factor analysis for prevention of complications are being initiated. As non-union in bone is a rare but very complex disease with dramatic socioeconomic impact for the healthcare system, many open questions arise which could be better understood by using methods of AI in the future. New fields of research applying AI models range from predictive models and cost analysis to personalized treatment strategies.

[Movement analysis and musculoskeletal simulation in non-union treatment-Experiences and first clinical results]. / Bewegungsanalyse und muskuloskeletale Simulation in der Pseudarthrosentherapie ­ Erfahrungen und erste klinische Ergebnisse.

BACKGROUND: The mechanical boundary conditions of the non-union and osteosynthetic construct are a key determinant of fracture healing after revision surgery. Aim of this study was to introduce a movement analysis and simulation workflow to determine the mechanical conditions during non-union healing in vivo. MATERIAL AND METHODS: On an individual case basis after non-union revision surgery we performed an accelerometry-based movement analysis. The results were then used as input for a musculoskeletal simulation of the non-union, osteosynthetic construct as well as adjacent joints mechanical boundary conditions. RESULTS: A total of 13 patients were analyzed with our new workflow. The introduced protocol allows an in vivo determination of the mechanical boundary conditions. On clinical follow-up all patients showed radiographic consolidation of the non-union. CONCLUSION: The introduced workflow allows a clinically applicable determination of the mechanical boundary conditions of fracture and non-union healing. Further studies can now determine the effect of the introduced technique for mechanically optimized postoperative aftercare regimes as well as biomechanically adapted surgical treatment.

Distance from the magnification device contributes to differences in lower leg length measured in patients with TSF correction.

INTRODUCTION: In absence of deformity or injury of the contralateral leg, the contralateral leg length is used to plan limb lengthening. Length variability on long-leg weight-bearing radiographs (LLR) can lead to inaccurate deformity correction. The aim of the study was to (1) examine the variability of the measured limb length on LLR and (2) to examine the influence of the position of the magnification device. MATERIALS AND METHODS: The limb lengths of 38 patients during deformity correction with a taylor-spatial-frame were measured retrospectively on 7.3 ± 2.6 (4-13) LLR per patient. The measured length of the untreated limb between LLR were used to determine length variability between LLR in each patient. To answer the secondary aim, we took LLR from a 90 cm validation distance. A magnification device was placed in different positions: at the middle of the 90 cm distance (z-position), 5 cm anterior and 5 cm posterior from the z-position, at the bottom and top of the validation distance as well as 5 cm medial and 15 cm lateral from the z-position. RESULTS: The measured length variability ranged within a patient from 10 to 50 mm. 76% of patients had a measured limb length difference of ≥ 2 cm between taken LLR. Compared to length measurement of the 90 cm test object with the magnification device in the z-position (90.1 cm), positioning the device 5 cm anterior led to smaller (88.6 cm) and 5 cm posterior led to larger measurements (91.7 cm). The measured length with the magnification device at the bottom, top, medial or lateral (90.4; 89.9; 90.2; 89.8 cm) to the object differed not relevantly. CONCLUSIONS: High variability of limb length between different LLR within one patient was observed. This can result from different positions of the magnification device in the sagittal plane. These small changes in positioning the device should be avoided to achieve accurate deformity correction and bone lengthening. This should be considered for all length and size measurements on radiographs.

Lunate morphology: association with the severity of scapholunate ligament injuries and carpal instability patterns.

Type II lunate has been associated with a lower incidence of dorsal intercalated segment instability (DISI) in the case of scapholunate dissociation. We aimed to evaluate the frequency of different lunate types and their influence on the prevalence and severity of scapholunate ligament (SLIL) injuries and the development of DISI. The surgical records of 414 arthroscopies were reviewed retrospectively. Lunate types were diagnosed based on radiograms and MRI examinations. The Type II lunate had a facet between hamate and lunate; in the Type I lunate, this facet is lacking. We additionally included the assessment of the capitate-triquetrum distance (CTD), which defines Type I, Intermediate, and Type II lunates. We adopted the DISI when the scapholunate angle was more than 80° and/or the radiolunate angle less than -15°. Fisher's exact test was applied to compare the distribution frequency of SLIL lesions and DISI deformity of patients with different lunate types. To quantify the inter- and the intra-rater reliability of lunate type assessment Cohen's kappa was calculated and, for CTD measurements, a Bland-Altman plot was created. Up to 77.1% patients had Type II lunates. Regarding MRI and CTD classification in patients with Type I lunates, Grade 4 SLIL injuries were more common than in those with Intermediate and Type II (p < 0.05). In the case of Grade 4 SLIL lesions, DISI was more common in patients with Type I lunates (p < 0.05). There were, however, only 25 patients with Type I lunates, and Grade 4 SLIL lesions according to MRI, and 6 according to CTD measurement.

CT in Patients With External Fixation for Complex Lower Extremity Fractures: Impact of Iterative Metal Artifact Reduction Techniques on Metal Artifact Burden and Subjective Quality.

BACKGROUND. Lower extremity external fixators have complex geometries that induce pronounced metal artifact on CT. Iterative metal artifact reduction (iMAR) algorithms help reduce such artifact, although no dedicated iMAR preset exists for external fixators. OBJECTIVE. The purpose of our study was to compare iMAR presets for CT examinations in terms of quantitative metal artifact burden and subjective image quality in patients with external fixators for complex lower extremity fractures. METHODS. This retrospective study included 72 CT examinations in 56 patients (20 women, 36 men; mean age, 56 ± 18 [SD] years) with lower extremity external fixators (regular, hybrid, or monotube). Examinations were reconstructed without iMAR (hereafter referred to as "noMAR") and with three iMAR presets (iMARspine, iMARhip, iMARextremity). A radiology resident quantified metal artifact burden using software. Two radiology residents independently assessed overall image quality and diagnostic confidence using 4-point scales (4 = excellent [highest quality or highest confidence]). Techniques were compared using Bonferroni-corrected post hoc tests. Interreader agreement was assessed by intraclass correlation coefficients (ICCs). A post hoc multinomial regression model was used for predicting overall image quality. RESULTS. Mean quantitative metal artifact burden was 100,816 ± 45,558 for noMAR, 88,889 ± 44,028 for iMARspine, 82,295 ± 41,983 for iMARhip, and 81,956 ± 41,890 for iMARextremity. Overall image quality yielded an ICC of 0.94 or greater. Using pooled reader data, median overall image quality score for the regular fixator was 2 (noMAR), 3 (iMARspine and iMARhip), and 4 (iMARextremity); for the hybrid fixator, 1 (noMAR), 2 (iMARspine), and 3 (iMARhip and iMARextremity); and for the monotube fixator, 2 (noMAR), 3 (iMARspine and iMARhip), and 4 (iMARextremity). Metal artifact burden was lower and overall image quality was higher (p < .05) for iMARhip and iMARextremity than noMAR and iMARspine for all fixators (aside from image quality of iMARhip and iMARextremity vs iMARspine for regular fixators) but were not different (all, p > .05) between iMARhip and iMARextremity. Median diagnostic confidence was 4 for all fixators and reconstructions. Independent predictors of overall quality relative to noMAR were iMARspine (odds ratio [OR] = 1.92-5.51), iMARhip (OR = 5.56-31.10), and iMARextremity (OR = 7.07-38.21). All iMAR presets introduced new reconstruction artifacts for all examinations for both readers. CONCLUSION. For the three fixator types, iMARhip and iMARextremity achieved greatest metal artifact burden reduction and highest subjective image quality, although both introduced new reconstruction artifacts. CLINICAL IMPACT. CT using the two identified iMAR presets may facilitate perioperative management of external fixators.

Radiation Dose Reduction in CT Torsion Measurement of the Lower Limb: Introduction of a New Ultra-Low Dose Protocol.

This study analyzed the radiation exposure of a new ultra-low dose (ULD) protocol compared to a high-quality (HQ) protocol for CT-torsion measurement of the lower limb. The analyzed patients (n = 60) were examined in the period March to October 2019. In total, 30 consecutive patients were examined with the HQ and 30 consecutive patients with the new ULD protocol comprising automatic tube voltage selection, automatic exposure control, and iterative image reconstruction algorithms. Radiation dose parameters as well as the contrast-to-noise ratio (CNR) and diagnostic confidence (DC; rated by two radiologists) were analyzed and potential predictor variables, such as body mass index and body volume, were assessed. The new ULD protocol resulted in significantly lower radiation dose parameters, with a reduction of the median total dose equivalent to 0.17 mSv in the ULD protocol compared to 4.37 mSv in the HQ protocol (p < 0.001). Both groups showed no significant differences in regard to other parameters (p = 0.344-0.923). CNR was 12.2% lower using the new ULD protocol (p = 0.033). DC was rated best by both readers in every HQ CT and in every ULD CT. The new ULD protocol for CT-torsion measurement of the lower limb resulted in a 96% decrease of radiation exposure down to the level of a single pelvic radiograph while maintaining good image quality.